IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/25682.html
   My bibliography  Save this paper

The Wrong Kind of AI? Artificial Intelligence and the Future of Labor Demand

Author

Listed:
  • Daron Acemoglu
  • Pascual Restrepo

Abstract

Artificial Intelligence is set to influence every aspect of our lives, not least the way production is organized. AI, as a technology platform, can automate tasks previously performed by labor or create new tasks and activities in which humans can be productively employed. Recent technological change has been biased towards automation, with insufficient focus on creating new tasks where labor can be productively employed. The consequences of this choice have been stagnating labor demand, declining labor share in national income, rising inequality and lower productivity growth. The current tendency is to develop AI in the direction of further automation, but this might mean missing out on the promise of the "right" kind of AI with better economic and social outcomes.

Suggested Citation

  • Daron Acemoglu & Pascual Restrepo, 2019. "The Wrong Kind of AI? Artificial Intelligence and the Future of Labor Demand," NBER Working Papers 25682, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:25682
    Note: LS
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w25682.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 113(4), pages 1091-1117.
    2. Olmstead, Alan L. & Rhode, Paul W., 2001. "Reshaping The Landscape: The Impact And Diffusion Of The Tractor In American Agriculture, 1910–1960," The Journal of Economic History, Cambridge University Press, vol. 61(3), pages 663-698, September.
    3. Mokyr, Joel, 1992. "The Lever of Riches: Technological Creativity and Economic Progress," OUP Catalogue, Oxford University Press, number 9780195074772.
    4. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    5. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    6. Karthik Muralidharan & Abhijeet Singh & Alejandro J. Ganimian, 2019. "Disrupting Education? Experimental Evidence on Technology-Aided Instruction in India," American Economic Review, American Economic Association, vol. 109(4), pages 1426-1460, April.
    7. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    8. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.),Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    9. Nelson, Richard R. & Winter, Sidney G., 1993. "In search of useful theory of innovation," Research Policy, Elsevier, vol. 22(2), pages 108-108, April.
    10. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    11. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    12. Mariana Mazzucato, 2015. "The Green Entrepreneurial State," SPRU Working Paper Series 2015-28, SPRU - Science Policy Research Unit, University of Sussex Business School.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. The Wrong Kind of AI? Artificial Intelligence and the Future of Labor Demand
      by maximorossi in NEP-LTV blog on 2019-05-14 14:30:41

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Judith Clifton & Amy Glasmeier & Mia Gray, 2020. "When machines think for us: the consequences for work and place," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 3-23.
    2. Anton Korinek, 2019. "Integrating Ethical Values and Economic Value to Steer Progress in Artificial Intelligence," NBER Working Papers 26130, National Bureau of Economic Research, Inc.
    3. Luigi Marengo, 2019. "Is this time different? A note on automation and labour in the fourth industrial revolution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 46(3), pages 323-331, September.
    4. Nippani, Abishek, 2020. "Automation and Labour in India: Policy Implications of Job Polarisation pre and post COVID-19 crisis," SocArXiv h9gaw, Center for Open Science.
    5. Atheendar S Venkataramani & Rourke O’Brien & Gregory L Whitehorn & Alexander C Tsai, 2020. "Economic influences on population health in the United States: Toward policymaking driven by data and evidence," PLOS Medicine, Public Library of Science, vol. 17(9), pages 1-17, September.

    More about this item

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:25682. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.